Efficient Scheme Research Articles

GCKSign: Simple and efficient signatures from generalized compact knapsack problems.

In 2009, Lyubashevsky proposed a lattice-based signature scheme using the Schnorr-like identification and the Fiat-Shamir heuristic and proved its security under the collision resistance of a generalized compact knapsack function. However, their security analysis requires the witness indistinguishability property, leading to significant inefficiency and an increase of sizes of public key and signature. To overcome the efficiency issue associated with the WI property, we introduce a new lattice-based assumption, called the target-modified one-wayness problem of the GCK function and show its reduction to well-known lattice-based problems. Additionally, we present a simple and efficient GCK-based signature scheme, GCKSign, whose security is based on the Module GCK-TMO problem in the random oracle model. GCKSign is a natural extension of Lyubashevsky's scheme in a module setting, but achieves considerable efficiency gains due to eliminating the witness indistinguishability property. As a result, GCKSign achieves approximately 3.4 times shorter signature size and 2.4 times shorter public key size at the same security level.

Escrow-free and efficient dynamic anonymous privacy-preserving batch verifiable authentication scheme for VANETs

To enhance road safety, Vehicular Ad-hoc Networks (VANETs) facilitate the exchange of safety-critical messages between smart vehicles and road traffic authorities. However, VANET’s wireless channels are prone to several attacks, such as replay or modification. Therefore, to protect the links, robust authentication and message integrity mechanisms are required. Previously, several robust authentication schemes have been devised. However, those designs often struggle with complex certificate management, the key escrow problem, and the necessity for secure channels to establish user keys. Additionally, prior methods rely on pseudonyms to ensure user privacy. To implement it, several pseudonyms are stored in the vehicle’s device, which burdens the device. To overcome these limitations, this study introduces an efficient and escrow-free dynamic anonymous authentication scheme tailored for VANETs. By utilizing the paradigm of certificate-based cryptography and fuzzy identity generation, the proposed design eliminates the limitations. Through rigorous security analysis, the proposed design’s effectiveness against various threats is demonstrated. Furthermore, a detailed performance analysis, including computational and communication cost comparisons, showcases the scheme’s feasibility for VANET deployment. An NS-3 simulation further confirms the suitability of the proposed scheme for real-world VANET communication scenarios.

Is adoption of modern dairy farming technologies interrelated? A case of smallholder dairy farmers in Meru county, Kenya

Attempts have been made to promote the adoption of modern dairy farming technologies (MDFT). However, the adoption of these technologies largely remains underutilized. This study aimed to analyze the determinants of the adoption of MDFTs in Meru County. Using purposive and proportionate sampling techniques from 355 smallholder dairy farmers in Meru County, Kenya, this study analyzed the factors that facilitate or impede the adoption of MDFTs. We use a Multivariate probit (MVP) to evaluate adoption decisions by dairy farm households facing multiple MDFTs. The results reveal a significant correlation among the eight MDFTs suggesting that modern technologies are interrelated. The MVP model results indicate that household income, education level, number of extension contacts, access to credit, farmer group membership, farming experience and livestock monetary value had positive effect on the adoption of MDFTs. Education level and extension contacts had a positive influence on the adoption of fodder establishment and preservation technologies. Farming experience in dairy farming had a positive effect on the adoption of well-structured and clean sleeping areas, and the growth of Rhodes grass. Household income had a positive effect on the growth of Rhodes grass and feed mixture. This work illustrates a need for a policy implication and insight into a need for the county government and private milk processing companies to increase extension frequency to enhance the adoption of MDFTs. Additionally, there is a need to increase access to affordable credit, this should be considered by the government by establishing strengthening a smallholder low-interest and efficient local credit schemes and institutions.

Resonance ionization spectroscopy of neodymium for determining a highly efficient two-step ionization scheme

Two-color two-step resonance ionization spectroscopy of neodymium (Nd) was performed to identify more than 120 even-parity autoionizing levels and their candidate J-values. The analysis of the observed autoionizing Rydberg series yielded a value of 44,560.11 (43)stat (2)sys cm−1 as a more accurate ionization potential of Nd. The saturation method was used to measure the transition cross-sections for some intense ionization transitions. From the measured cross-sections, the ionization efficiencies of some two-step ionization schemes were evaluated using the scheme cross-section formula to obtain several promising schemes.

A Secure and Efficient Authentication Scheme for Large-Scale IoT Devices Based on Zero-Knowledge Proof

A Secure and Efficient Authentication Scheme for Large-Scale IoT Devices Based on Zero-Knowledge Proof

Blockchain-enhanced efficient and anonymous certificateless signature scheme and its application

Although the Internet of Things (IoT) brings efficiency and convenience to various aspects of people’s lives, security and privacy concerns persist as significant challenges. Certificateless Signatures eliminate digital certificate management and key escrow issues and can be well embedded in resource-constrained IoT devices for secure access control. Recently, Ma et al. designed an efficient and pair-free certificateless signature (CLS) scheme for IoT deployment. Unfortunately, We demonstrate that the scheme proposed by Ma et al. is susceptible to signature forgery attacks by Type-II adversaries. That is, a malicious-and-passive key generation center (KGC) can forge a legitimate signature for any message by modifying the system parameters without the user’s secret value. Therefore, their identity authentication scheme designed based on vehicular ad-hoc networks also cannot guarantee the claimed security. To address the security vulnerabilities, we designed a blockchain-enhanced and anonymous CLS scheme and proved its security under the Elliptic curve discrete logarithm (ECDL) hardness assumption. Compared to similar schemes, our enhanced scheme offers notable advantages in computational efficiency and communication overhead, as well as stronger security. In addition, a mutual authentication scheme that satisfies the cross-domain scenario is proposed to facilitate efficient mutual authentication and negotiated session key generation between smart devices and edge servers in different edge networks. Performance evaluation shows that our protocol achieves an effective trade-off between security and compute performance, with better applicability in IoT scenarios.

Efficient provable dual receiver hybrid and light weight public key schemes based on the discrete logarithm problem without pairings

AbstractDual‐receiver proxy re‐encryption is a cryptographic technique that enables secure data sharing among multiple authorized users or entities. It has gained significant attention for its ability to manage access permissions, data confidentiality, and streamline communication channels. These schemes have been widely used in various applications, including healthcare systems, cloud computing, Internet of Things (IoT) systems, collaborative environments, and secure communication channels. This paper aims to propose two proxy re‐encryption schemes for dual receivers without pairings. The first is dual receiver lightweight proxy re‐encryption without pairings (DR‐LWPRE‐WP), which uses a public key scheme to reduce computational complexity. The second is dual receiver hybrid proxy re‐encryption without pairings (DR‐HPRE‐WP), which incorporates public key and symmetric key schemes. Both schemes offer protection against selected plaintext attacks based on the decisional Diffie‐Hellman principle. The DR‐LWPRE‐WP scheme reduces computation by approximately 53% compared to pairing‐based schemes, making it suitable for lightweight applications like the Internet of Things. The computational efficacy of these schemes offers significant benefits for resource‐constrained environments and practical implementations.

Numerical modeling of transient water table in shallow unconfined aquifers: A hyperbolic theory and well-balanced finite volume scheme

We present a new methodology capable of modeling transient motion of shallow phreatic surface of groundwater in unconfined aquifers. This methodology is founded on a new and comprehensive theory for water table motion and a corresponding efficient numerical scheme. In the theoretical aspect, we derived a new set of governing equations constituted by a depth-averaged continuity equation and momentum equations based on unsteady Darcy’s law. The derived governing equations are of the hyperbolic type and possess stiff terms in the momentum equations due to the inertia motion in a characteristic time scale that is relatively shorter than the time scale of seepage motion. To effectively solve the derived hyperbolic system with stiff terms, in the numerical aspect, we utilize f-wave propagation algorithm, an explicit finite volume method, that can ensure numerical convergence and well-balancing solutions when momentum is rapidly relaxing to an equilibrium of steady state. Verification is successfully performed by comparing the results with analytic solutions to the classic problem of multidimensional spreading of a groundwater mound. This study demonstrates that the proposed methodology can accurately and satisfactorily simulate the spatiotemporal distribution of shallow water table and its wetting front in unconfined aquifers.

A Mode Evolution Metric to Extract Reaction Coordinates for Biomolecular Conformational Transitions.

The complex, multidimensional energy landscape of biomolecules makes the extraction of suitable, nonintuitive collective variables (CVs) that describe their conformational transitions challenging. At present, dimensionality reduction approaches and machine learning (ML) schemes are employed to obtain CVs from molecular dynamics (MD)/Monte Carlo (MC) trajectories or structural databanks for biomolecules. However, minimum sampling conditions to generate reliable CVs that accurately describe the underlying energy landscape remain unclear. Here, we address this issue by developing a Mode evolution Metric (MeM) to extract CVs that can pinpoint new states and describe local transitions in the vicinity of a reference minimum from nonequilibrated MD/MC trajectories. We present a general mathematical formulation of MeM for both statistical dimensionality reduction and machine learning approaches. Application of MeM to MC trajectories of model potential energy landscapes and MD trajectories of solvated alanine dipeptide reveals that the principal components which locate new states in the vicinity of a reference minimum emerge well before the trajectories locally equilibrate between the associated states. Finally, we demonstrate a possible application of MeM in designing efficient biased sampling schemes to construct accurate energy landscape slices that link transitions between states. MeM can help speed up the search for new minima around a biomolecular conformational state and enable the accurate estimation of thermodynamics for states lying on the energy landscape and the description of associated transitions.

Performance evaluation and analysis of public-key schemes in embedded IoT devices

The Internet of Things (IoT) is considered one of the emerging technologies that have attracted widespread attention from industry and academia as a result of their ability to use them in many applications, including military, healthcare, and industrial control. The inherent vulnerabilities in communications of IoT networks, which consist of resource-constrained devices, pose significant security challenges. To protect sensitive data exchanged within these networks, it is necessary to design and implement lightweight and efficient cryptographic schemes that consider resource-constrained IoT devices. This paper evaluates the performance of five well-known public-key schemes on three real-world IoT devices including IOTLAB-M3, Arduino-Zero, and Decawave DWM1001. The examined public-key schemes are categorized into two classes: integer factorization-based (RSA and Rabin schemes) and elliptic curve-based (ECIES, ECDH, and ECDSA schemes). By conducting comprehensive experiments, we compare these schemes in terms of computational time and energy consumption, providing valuable insights for selecting optimal public-key schemes in resource-constrained IoT environments.

Enhancing lepidolite flotation efficiency with the novel LCJ collector: comparative analysis and mechanistic insights in Jiangxi Province’s lepidolite resources

ABSTRACT This study evaluates the flotation performance of a novel combination collector, LCJ, on lepidolite from Jiangxi Province, China. A comparative analysis with the on-site collector EO demonstrates an economically efficient separation scheme for lepidolite. Results show that LCJ outperforms EO in capturing lepidolite. Employing 400 g/t sodium hexametaphosphate as an inhibitor and 290 g/t LCJ as a collector, a flotation process with one rougher, two cleaner, and two scavenger stages achieves a lepidolite concentrate with a Li2O grade of 2.10% and a recovery of 78.62%. LCJ also enhances foamability within conventional air-inflation ranges. Infrared testing, Zeta potential analysis, and contact angle measurements indicate similar organic adsorption on the lepidolite surface for both collectors. However, LCJ significantly influences the Zeta potential, increasing hydrophobicity. These findings confirm LCJ as an efficient and selective collector for lepidolite flotation, with promising application prospects.

Using TiO2 to capture hot electrons for self-powered position-sensitive photodetection.

As environmental issues arise, the demand for self-powered position-sensitive detectors (PSDs) is increasing because of their advantages in miniaturization and low power consumption. Finding higher efficiency schemes for energy conversion is paramount for realizing high-performance self-powered PSDs. Here, a surface plasmon-based approach was used to improve the energy conversion efficiency, and a plasmon-enhanced lateral photovoltaic effect (LPE) was observed in PSD with TiO2/Au nanorods (NRs)/Si structure. The Au NRs convert absorbed light energy into electricity by generating hot electrons, which are efficiently captured by the TiO2 layer, and the PSD is capable of generating position sensitivity as high as 251.75 mV/mm when illuminated by a 780 nm laser without any external power supply, i.e. about five times higher than similar sensors in previous studies. In addition, the position sensitivity can be tailored by the thickness of TiO2 films. The enhancement mechanism is investigated by a localized surface plasmon (LSP)-driven carrier diffusion model. These findings reveal an important strategy for high sensitivity and low energy cost PSDs while opening up new avenues for energy harvesting self-powered position sensors.

FOC-PH-CP-ABE: An Efficient CP-ABE Scheme With Fully Outsourced Computation and Policy Hidden in the Industrial Internet of Things

FOC-PH-CP-ABE: An Efficient CP-ABE Scheme With Fully Outsourced Computation and Policy Hidden in the Industrial Internet of Things

Binary Particle Swarm Optimization for Fair User Association in Network Slicing-Enabled Heterogeneous O-RANs

The Open-Radio Access Network (O-RAN) alliance is leading the evolution of telecommunications towards a greater intelligence, openness, virtualization, and interoperability within mobile networks. The O-RAN standard incorporates of many components the Open-Central Unit (O-CU) and Open-Distributed Unit (O-DU), network slicing and heterogeneous base stations (BS). Together, these innovations have given rise to a three-tiered user association (UA) relationship in a type of network called heterogeneous network (HetNet) with network slicing-enabled. There is an absence of efficient UA schemes for achieving fair resource allocation in such network scenario. Hence, this study formulates the fairness-aware UA problem as a utility-based combinatorial optimization problem, which is computationally hard to solve. Hence, an efficient Binary Particle Swarm Optimization (BPSO)-based UA scheme is proposed to solve the problem. Through simulations of an O-RAN based HetNet with network slicing-enabled, performance of the proposed BPSO-UA scheme is compared against two other baseline UA schemes. Results demonstrate the effectiveness of the proposed BPSO-UA scheme in achieving high fairness through equitable network slicing resource allocation, thereby leading to higher user connectivity rate and comparable average spectral efficiency. This innovative approach sheds light on the potential of metaheuristic algorithms in tackling intricate UA challenges, offering valuable insights for the future design and optimization of mobile networks.

SEAIS: Secure and Efficient Agricultural Image Storage Combining Blockchain and Satellite Networks

The image integrity of real-time monitoring is crucial for monitoring crop growth, helping farmers and researchers improve production efficiency and crop yields. Unfortunately, existing schemes just focus on ground equipment and drone imaging, neglecting satellite networks in remote or extreme environments. Given that satellite internet features wide area coverage, we propose SEAIS, a secure and efficient agricultural image storage scheme combining blockchain and satellite networks. SEAIS presents the mathematical model of image processing and transmission based on satellite networks. Moreover, to ensure the integrity and authenticity of image data during pre-processing such as denoising and enhancement, SEAIS includes a secure agricultural image storage and verification method based on blockchain, homomorphic encryption, and zero-knowledge proof. Specifically, images are stored via IPFS, with hash values and metadata recorded on the blockchain, ensuring immutability and transparency. The simulation results show that SEAIS exhibits more stable and efficient processing times in extreme environments. Also, it maintains low on-chain storage overhead, enhancing scalability.

Fifth-Kind Chebyshev Spectral Collocation Treatment for the Volterra Integro-Differential Equation of the Third Kind

In this research work, we offer an efficient spectral numerical scheme for handling the Volterra integro-differential of the third kind via Chebyshev polynomials of the fifth kind. The celebrated fundamentals and relations were stated with some details. With the aid of the spectral collocation method and the properties of Chebyshev polynomials, the singular Volterra integro-differential equation with its initial condition was transformed into a system of algebraic equations. The convergence and error analyses were discussed in depth. The validity and applicability of the method were tested and verified through three numerical examples, with the absolute errors reported in tables an graphs.

Sustainable and efficient separation of ternary multi-azeotropic mixture butanone/ethanol/water based on the intensified reactive extractive distillation: process design, multi-objective optimization, and multi-criteria decision-making

It is of great significance and necessity to develop a sustainable and efficient separation scheme of butanone (MEK), ethanol (EtOH), and water, which are usually formed during the cinepazide maleate synthesis process. To the best of our knowledge, the systematic separation of this ternary multi-azeotropic mixture remains comparatively less studied, compounded by the significant challenges posed by its intricate composition comprising four azeotropes and three distillation boundaries. Therefore, a systematic approach by integrating the process design, multi-objective optimization, and multi-criteria decision-making (MCDM) methods was proposed to achieve the sustainable separation. Initially, three separation schemes, i.e., triple-column extractive distillation (TCED), double-column reactive extractive distillation (DCRED), and side stream intensified double-column reactive extractive distillation (SS-DCRED), were mainly explored via the thermodynamic and kinetic analysis. Subsequently, the multi-objective particle swarm optimization (MOPSO) algorithm was employed to optimize the process based on three objectives namely the total annual cost (TAC), CO2 emissions, and process route index (PRI). Finally, an efficient MCDM method combining CRITIC and TOPSIS was employed to rank the Pareto front solutions of the corresponding process design. Based on the comparison results, the optimal TCED process exhibits the lowest PRI with a decrease of 50.61% and 55.06% compared to that of the SS-DCRED and the DCRED, respectively. It also shows the best performance simultaneously considering economic, environmental, and safety criteria. Of note, the SS-DCRED separation process exhibited the lowest TAC, with a decrease of 60.67% and 11.45% compared to that of the TCED and the DCRED, respectively.

Scalable multiphoton generation from cavity-synchronized single-photon sources

We propose an efficient, scalable, and deterministic scheme to generate multiple indistinguishable photons over independent channels, on demand. Our design relies on multiple single-photon sources, each coupled to a waveguide, all interacting with a common cavity mode. The cavity synchronizes and triggers the simultaneous emission of one photon by each source, which are collected by the waveguides. In a state-of-the-art circuit QED implementation, this scheme supports the creation of single photons with 99% purity, indistinguishability, and efficiency at rates of ∼MHz. We also discuss conditions to produce up to 100 photons simultaneously with generation rates of hundreds of kHz. This is orders of magnitude more efficient than previous demultiplexed sources for boson sampling and enables the realization of deterministic multiphoton sources and scalable quantum information processing with photons. Published by the American Physical Society 2024

A reliable Bayesian regularization neural network approach to solve the global stability of infectious disease model

The purpose of this study is to perform the numerical results of the global stability of infectious disease mathematical model by using the stochastic computing scheme. The design of proposed solver is presented by one of the efficient and reliable schemes named as Bayesian regularization neural network (BRNN). The global stability of infectious disease mathematical nonlinear model is categorized into susceptible, infected, recovered and vaccinated. The construction of dataset is performed through the Runge-Kutta scheme in order to lessen the mean square error (MSE) by dividing the statics as training 74 %, while 13 % for both testing and endorsement. The proposed stochastic process contains log-sigmoid merit function, twenty neurons and optimization through RBNN for the numerical solutions of the global stability of infectious disease mathematical system. The best training values for each model's case are performed around 10–11. The scheme's correctness is performed by the matching of the results and the minor calculated absolute error performances. Moreover, the regression, state transmission, error histogram and MSE indicate the trustworthiness of the designed solver.

Efficient high-order operator-splitting schemes for solving the time-dependent Schrödinger equation

Several fourth-order symmetric operator-splitting schemes with four and five stages for solving the time-dependent Schrödinger equation have been proposed. These schemes have been studied and compared with some optimal fourth- and sixth-order operator split schemes reported in the literature using a one-dimensional model and several realistic three-dimensional triatomic reactive scattering problems in Jacobi coordinates. Two new fourth-order operator-splitting schemes with four and five stages, which are more efficient than previously reported schemes, are recommended for the realistic numerical solution of the time-dependent Schrödinger equation in the field of molecular dynamics. It was found that the order-preserving method proposed by McLachlan works well for three-dimensional triatomic reactive scattering problems in Jacobi coordinates, despite the complicated form of the Hamiltonian.